Evidence map›Paper›PMID 40034277›Full record

ArticleHeliyon2025

Blood-based biomarkers derived from tumor-informed DNA methylation analysis for lung adenocarcinoma.

Pitaksin Chitta, Timothy M Barrow, Atchara Dawangpa, David C Christiani, Naravat Poungvarin, Chanachai Sae-Lee

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Article in Heliyon, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Pitaksin ChittaResearch Division, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand.
Timothy M BarrowSchool of Life Sciences, University of Essex, Colchester, United Kingdom.
Atchara DawangpaResearch Division, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand.
David C ChristianiHarvard T H Chan School of Public Health, Massachusetts General Hospital/Harvard Medical School, Boston, MA, USA.
Naravat PoungvarinClinical Pathology, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand.
Chanachai Sae-LeeResearch Division, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand.

Funding

The Boston Lung Cancer Survival CohortU01CA209414 · NCI · HARVARD UNIVERSITY D/B/A HARVARD SCHOOL OF PUBLIC HEALTH · PI David C Christiani · 2017 to 2026
$12.2M
Statistical Methods for Analysis of Massive Genetic and Genomic Data in Cancer ResearchR35CA197449 · NCI · HARVARD UNIVERSITY D/B/A HARVARD SCHOOL OF PUBLIC HEALTH · PI XIHONG LIN · 2015 to 2026
$10.9M
NCI NIH HHS R35 CA197449NCI NIH HHS U01 CA209414
6 · The paper itself

Abstract

Objective: To identify robust markers of lung adenocarcinoma (LUAD) using DNA methylation profiles from blood samples informed by tissue lung adenocarcinoma. Methods: This study analyzed 56 LUAD blood samples from patients attending clinic at Siriraj Hospital, Thailand and 51 samples from healthy participants, using 644 tumor and 59 normal tissue methylome datasets from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases for candidate gene identification. We performed comparative analysis to identify DNA methylation (DNAm) changes present in tumors that are also observable in blood, to be taken forward for validation. Results: DNAm profiling of lung tumor datasets identified 59,639 differentially methylated positions (DMPs), of which 17,251 exhibited a negative correlation with gene expression. In blood samples, 46,680 DMPs were identified among LUAD patients, which were enriched in pathways associated with the ribosome, spliceosome, cell cycle, ubiquitin mediated proteolysis and nucleocytoplasmic transport. Comparative analysis revealed a two DMP epigenetic signature of matching changes in both tissue and blood. This signature offered high diagnostic performance in distinguishing LUAD from normal lung tissue (AUC: 0.77-0.91) and in blood samples from LUAD patients (AUC:0.92-0.96). Similarly high performance was observed in two independent tissue validation datasets (AUC:0.90-0.92). Conclusions: Our novel two DMP signatures offer robust performance in both lung tissue and blood for the identification of LUAD.

Indexed as

BiomarkersBloodDNA methylationLung adenocarcinomaMolecular epidemiologyTissue

Identifiers

PMID40034277
PMCPMC11874551

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.